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Multi-way modelling of oral microbial dynamics and host-microbiome interactions during induced gingivitis
G R van der Ploeg1, B W Brandt2, B J F Keijser3
1Biosystems Data Analysis, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.
NPJ Biofilms and Microbiomes
|September 19, 2024
Summary
Gingivitis, a reversible gum inflammation, is linked to oral microbiome and metabolome changes. This study reveals microbial communities and metabolic pathways associated with gingivitis severity in healthy individuals.
Area of Science:
- Oral microbiology
- Metabolomics
- Periodontal disease research
Background:
- Gingivitis, an early stage of periodontal disease, is characterized by reversible gum inflammation.
- While often linked to poor oral hygiene and plaque, gingivitis susceptibility is influenced by complex host-microbiome-metabolome interactions.
- Understanding these interactions is crucial for developing targeted interventions.
Purpose of the Study:
- To investigate the dynamic interplay between the oral microbiome and salivary metabolome during experimental gingivitis.
- To identify specific microbial subcommunities and metabolic pathways associated with the severity of gingivitis.
- To explore the relationship between host factors, oral microbiota, and metabolic changes in gingivitis development.
Main Methods:
- Utilized Parallel Factor Analysis (PARAFAC) to model multi-way data from 41 systemically healthy participants undergoing experimental gingivitis.
- Analyzed dynamics of oral microbiome composition and salivary metabolome over time.
- Integrated predicted microbial metabolic functions with measured salivary metabolome data.
Main Results:
- Identified distinct microbial subcommunities exhibiting similar dynamic patterns correlated with gingivitis magnitude.
- Revealed key metabolic pathways linked to shifts in Gram-positive/Gram-negative bacteria proportions and anaerobic bacteria variations.
- Demonstrated connections between microbial dynamics, metabolic changes, biofilm formation, and virulence factors in experimental gingivitis.
Conclusions:
- Oral microbiome and salivary metabolome dynamics are intricately linked to gingivitis development and severity.
- PARAFAC analysis effectively models complex interactions, identifying microbial and metabolic signatures of gingivitis.
- Findings provide insights into the pathogenesis of gingivitis, highlighting potential targets for prevention and treatment.
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